When variants lack semantic equivalence: Adverbial Subclause Word Order

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This chapter argues that it will make results of variationist studies more relevant for linguistic theory if internal predictors assumed to constrain syntactic variation are operationalized in a way that explicitly relates them to semantic or—more broadly—functional hypotheses. We use word order in Danish adverbial subordinate clauses as a case study for how a hypothesized semantic difference between variants can be operationalized. This word order alternation concerns the relative placement of sentential adverbials and finite verbs in subclauses. While the variable is structurally well-defined (Adverb<Verb vs. Verb>Adverb), it challenges classic theoretical and methodological assumptions in variationist studies by entailing a semantic difference, since the two word orders conveying subtly different meanings when used in subclauses. For this study, we operationalize a set of linguistic predictors related to the two most prevalent meaning hypotheses given in the literature, the Assertivity and the Foregrounding Hypothesis. Mixed-effect models and random forest analyses are used to examine the effects and strength of intra- and extralinguistic (social) predictors. Geographical differences related with social stratification indicate an ongoing standardization process emanating from the capital of Copenhagen. The import of our findings related to linguistic theory is discussed.
Translated title of the contributionNår varianter ikke er semantisk ækvivalente
Original languageEnglish
Title of host publicationExplanations in Sociosyntactic Variation
Number of pages35
Place of PublicationCambridge
PublisherCambridge University Press
Publication date2022
ISBN (Print)9781108492843
ISBN (Electronic)9781108674942
Publication statusPublished - 2022
SeriesStudies in Language Variation and Change

    Research areas

  • Faculty of Humanities - syntactic variation, subordinate clauses, adverbial clauses, Word order, functional linguistics, mixed effects models, random forest analysis, Danish, LANCHART

ID: 181235150